Find Academic Supervisors

• Computational Fluid Dynamics
• Spectral Element Method
• Large Eddy Simulation
• +3 more

Paul Fischer is a Professor at the University of Illinois, holding dual appointments in the Siebel School of Computing and Data Science and the Mechanical Science and Engineering department. His research focuses on advanced numerical methods for fluid dynamics, particularly leveraging spectral element techniques and high-performance computing. He is a core contributor to the Nek5000/NekRS computational frameworks. Recent work emphasizes turbulence modeling, exascale CFD simulations, and multiphase flow dynamics in complex systems like pebble bed reactors. His research interests span spectral methods, large eddy simulation (LES), direct numerical simulation (DNS), and parallel computing architectures. Key projects include developing scalable algorithms for Reynolds-averaged Navier-Stokes (RANS) models and exploring non-conforming domain decomposition approaches for reacting flows. His contributions bridge computational methodology and engineering applications, with a focus on exascale-ready solutions. Publications from 2024-2025 highlight advancements in energy-efficient CFD simulations, turbulence transition mechanisms in granular media, and reduced order modeling for turbulent flows. Collaborations involve cross-disciplinary teams focusing on combustion, fluid-structure interaction, and high-fidelity flow analysis. He maintains active involvement in computational fluid dynamics communities and contributes to open-source software tools critical for industrial and academic research. Current efforts prioritize scalability, accuracy, and adaptability in numerical methods for next-generation supercomputing platforms.

• Database Systems
• Data Management
• Scientific Data Processing
• +5 more

Dr. Martin L. Kersten is a leading figure in database systems research at the Centrum Wiskunde & Informatica (CWI) in Amsterdam, Netherlands. With over three decades of contributions, his work focuses on column-oriented database architectures, scientific data management, and query optimization. Key Research Areas: Database systems, big data processing, query performance analysis, data-intensive scientific applications Projects: MonetDB, SciQL, TELEIOS, ExaNeSt His recent publications emphasize in-database machine learning , query log mining , and exascale computing . He pioneered database cracking and intermediate recycling techniques to enhance query processing efficiency. 2014 SIGMOD Edgar F. Codd Innovations Award for groundbreaking contributions to database technology Collaborations span institutions like ICDE , VLD , and EuroSys workshops. His work bridges theoretical advancements with practical implementations for scientific and industrial applications.

Mark AinsworthView profile

Professor

• Numerical Approximation of Partial Differential Equations
• A Posteriori Error Estimation
• High Order Finite Element Methods
• +5 more

Mark Ainsworth is a Francis Wayland Professor of Applied Mathematics at Brown University and holds a joint faculty appointment with Oak Ridge National Laboratory. He obtained his PhD from Durham University (1989) and has held prominent roles such as Director of the Centre for Numerical Algorithms and Intelligent Software (2011-2012). His research focuses on numerical analysis, particularly finite element methods for partial differential equations, a posteriori error estimation, and high-performance computing challenges like resiliency on exascale systems. Education: PhD in Mathematics, Durham University, 1989 BSc in Mathematics, Durham University, 1986 Research Interests: Numerical approximation of PDEs A posteriori error estimation and adaptive methods High order finite element methods Resiliency of numerical algorithms on emerging architectures Fractional PDEs and scientific data compression Awards: SIAM Fellow (2014) FIMA (2010) Whitehead Prize (2004) J.L. Lions Prize (2004) Fellow of Royal Society of Edinburgh (2003) Grants & Leadership: Co-PI for ARO MURI on fractional PDEs (2015-2020) Directed NAIS center (2011-2012), a £5M multi-institutional initiative Organized major international conferences on computational mathematics Labs/Teams: Collaborations include Oak Ridge National Lab and international research networks in numerical analysis and scientific computing.

Tobias NeckelView profile

Associate Professor

• Uncertainty Quantification
• Random Differential Equations
• Numerical Algorithms
• +4 more

Tobias Neckel is an Associate Professor at the Institute for Informatics at the Technical University of Munich (TUM), where he leads research projects and coordinates academic programs. He has been the project team leader of the IGGSE Project ExaNIML since 2018, main coordinator of the Ferienakademie since 2014, and Program Coordinator of the Bavarian Graduate School of Computational Engineering (BGCE) since 2009. Diploma in Technomathematik from TU München (2005) Dr. rer. nat. in Informatics from TU München (2009) Neckel's research focuses on Uncertainty Quantification, Random Differential Equations, and High Performance Computing. His work develops efficient numerical algorithms using hierarchic and adaptive methods such as octrees/spacetrees and sparse grids, with applications in fluid-structure interactions and incompressible fluid flow simulation. His research bridges theoretical mathematics with practical computational science, emphasizing robust and efficient implementations. His recent publications demonstrate a strong trajectory in multi-fidelity modeling, uncertainty quantification, and high-performance computing. Neckel has made significant contributions to scalable hierarchical approximation methods, dynamic resource management in HPC, and the application of machine learning techniques to computational science problems. His work spans diverse application domains including plasma physics, hydrology, and computational engineering. Lehrfonds prize of the TUM (2014) Ernst Otto Fischer prize of the TUM (2011) Promotionspreis des Bunds der Freunde der TU München (2009) Neckel has supervised numerous graduate students and has been actively involved in curriculum development and teaching innovation. His book "Bits and Bugs: A Scientific and Historical Review of Software Failures in Computational Science" (2019) represents a significant contribution to understanding software reliability in scientific computing. He has organized minisymposia at major conferences including SIAM CSE and SIAM UQ, and serves on program committees for various computational science conferences. As coordinator of the Ferienakademie and the BGCE, Neckel plays a central role in advanced computational engineering education in Bavaria. His research group develops software for exascale computing and contributes to the Transregional Collaborative Research Centre 89 on Invasive Computing. Neckel also maintains international collaborations, with research stays at institutions including the Australian National University and Tokyo Institute of Technology.

Aiichiro NakanoView profile

Professor

• Computational Science
• Scientific Machine Learning
• Materials Simulation
• +2 more

Aiichiro Nakano is Professor of Computer Science with joint appointments in Physics & Astronomy, Quantitative & Computational Biology, and the Collaboratory for Advanced Computing and Simulations at USC. He holds a Ph.D. in physics from University of Tokyo (1989) and has authored over 485 refereed publications in scalable algorithms, scientific machine learning, and computational materials science. Research develops AI-driven simulation methods for materials discovery, quantum computing applications, and exascale molecular dynamics. Recent work focuses on foundation models for molecular simulations, high-energy-density polymers, and nanocatalysis under extreme conditions. Publications show consistent contributions to computational science infrastructure, with accelerating focus on machine learning interatomic potentials and quantum-classical computing integration. Research bridges theoretical development with high-performance computing implementations. National Science Foundation CAREER Award

Mateo Valero CortésView profile

Professor

• Computer Architecture
• High-Performance Computing
• Parallel Computing
• +3 more

Mateo Valero Cortés is a renowned Professor of Computer Architecture at the Polytechnic University of Catalonia and Director of the Barcelona Supercomputing Center (BSC). He has held academic and leadership roles since 1974, advancing high-performance computing (HPC) and computer architecture research. His work includes pioneering contributions to vector architectures, multithreading, and instruction-level parallelism. Education includes a Telecommunications Engineering degree from the Polytechnic University of Madrid (1974) and a PhD in Telecommunications Engineering from the Polytechnic University of Catalonia (1980). His research spans over 700 publications, focusing on HPC systems, parallel computing, and supercomputing infrastructure. Key research interests include vector processing, super-scalar processors, and task-based programming models. Recent work emphasizes scalable architectures for exascale computing and energy-efficient hardware-software co-design. Notable achievements include the Eckert-Mauchly Prize (highest in computer architecture), Seymour Cray Award, and Charles Babbage Prize. He has led initiatives like the Spanish Supercomputing Network (RES) and PRACE (European HPC partnership). Academic affiliations include the Royal Academy of Engineering of Spain, ACM Fellow, and IEEE Fellow. He has received 13 honorary doctorates and awards such as Mexico’s Order of the Aztec Eagle. Current projects include the Mont-Blanc HPC prototype and ERC-funded research on multi-core chip design. His BSC oversees over 300 researchers and manages MareNostrum supercomputers.

• Computer Architecture
• Reconfigurable Computing
• Network-on-Chip (NoC)
• +7 more

Ioannis Sourdis is a Full Professor at the Department of Computer Engineering, Chalmers University of Technology, Sweden. His research focuses on computer architecture, reconfigurable computing, network-on-chip (NoC) design, memory systems, and fault-tolerant embedded systems, with applications in biomedical informatics and hardware security. Current projects include EUMMSS (Efficient Uncore Mechanisms for Multicore Space Systems, funded by the Swedish National Space Board) and eProcessor (European Processor Ecosystem, funded by the European Commission). Past initiatives include the DeSyRe project (on-demand system reliability), ECOSCALE (exascale reconfigurable computing), and SHARCS (secure hardware-software architectures). His work spans NoC router design (e.g., FastTrackNoC, DDRNoC), memory compression (MemSZ, L2C), and biomedical security applications (heartbeat-based protocols). He has published extensively in venues like DATE, ICS, PACT, and IEEE Transactions on Networking. Key research areas: Chiplet-based systems , hybrid memory architectures , FPGA acceleration , and real-time stream aggregation .

Vivek SarkarView profile

Professor

• Parallel Computing
• Programming Languages
• Compilers
• +5 more

Vivek Sarkar is the John P. Imlay, Jr. Dean of the College of Computing at Georgia Institute of Technology and a professor in the School of Computer Science. He leads the Habanero Extreme Scale Software Research Laboratory, focusing on parallel computing, programming languages, compilers, and runtime systems. Previously, he was a Professor and Chair of Computer Science at Rice University and held senior roles at IBM Research, where he contributed to projects like the X10 programming language and the Jikes Research Virtual Machine. Research Interests: His work spans parallel computing software, including programming languages (e.g., X10, Habanero-Java), compiler optimizations, runtime systems, and debugging tools for high-performance systems. He emphasizes scalability and correctness in distributed and heterogeneous environments. Awards & Affiliations: ACM Fellow (2008), IEEE Fellow, Ken Kennedy Award (2011), member of the US Department of Energy’s ASCAC, and former IBM Academy of Technology member. He chairs the Center for Research into Novel Computing Hierarchies (CRNCH) at Georgia Tech. Grants & Students: His research is supported by NSF grants. He advises students in parallel computing, with openings for researchers interested in his lab’s work on asynchronous systems, graph processing, and quantum-classical programming. Labs & Projects: Habanero Lab, CRNCH, and collaborations on Chapel runtime systems, actor-based programming models, and exascale computing challenges.

Ryan M. PollyeaView profile

Associate Professor

• Geofluids
• Energy Resources
• Geologic CO2 Sequestration
• +4 more

Ryan M. Pollyea is an Associate Professor in the Department of Geosciences at Virginia Tech’s College of Science. His research focuses on geofluids, energy resources, and geologic CO2 sequestration, with expertise in numerical modeling of fluid flow in porous media and geospatial analysis. He leads the VT Hydrogeosciences Lab, investigating processes like CO2 sequestration in basalt reservoirs and fluid-induced seismicity linked to wastewater injection. Education: Ph.D., University of Idaho (2012); B.S., University of Dayton (1999). His team includes PhD student Wu Hao and MS student Gradyon Konzen, studying topics like capillary pressure uncertainty and hydraulic effects of wastewater injection. Research interests span coupled thermal-hydro-chemical-mechanical modeling, fracture network characterization via LiDAR, and reservoir-scale permeability changes. He emphasizes applying computational methods to address energy and environmental challenges, with a focus on carbon storage and induced seismicity mitigation. Teaching includes courses like Groundwater Hydrology, Reactive Transport Modeling, and Engineering Geology. His work integrates high-performance computing and machine learning to analyze large datasets, exemplified by collaborations on exascale simulation frameworks and semantic interaction tools for ensemble analysis. Current projects include the Virginia SWIFT initiative, assessing aquifer recharge risks, and evaluating carbon storage potential in basaltic formations. His lab’s research underscores the interplay between subsurface fluid dynamics and geological processes, with applications to sustainable energy and environmental management.

Charles GillanView profile

Senior Lecturer

• High Performance Computing (HPC)
• Artificial Intelligence (AI) in Healthcare
• Quantum Computing
• +4 more

Charles Gillan is a Senior Lecturer at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science, affiliated with the High Performance and Distributed Computing department and the Institute of Electronics, Communications & Information Technology. His research bridges HPC systems, AI applications in healthcare, and computational physics. Key projects include managing ICU patient care via neural networks, exascale-ready mathematical packages, and edge computing architectures. Research interests focus on high-performance computing (HPC), quantum computing, real-time data analytics, and electron-molecule scattering simulations. Notable contributions include developing microserver architectures for edge analytics and advancing AI-driven clinical decision support systems. Gillan has collaborated on interdisciplinary projects like food authenticity testing using spectroscopy and improving ventilator management in intensive care units. Publications span AI in healthcare, HPC system design, and computational methods for physics problems. He has secured funding for initiatives such as the KTP partnership with Foods Connected Ltd and the HANDHELD olfactory detection project. Gillan's work emphasizes practical applications of advanced computing across healthcare, engineering, and cybersecurity domains.

Thomas LudwigView profile

Professor

• High-Performance Computing (HPC)
• Data Storage Systems
• Energy Efficiency in Computing
• +3 more

Prof. Dr. Thomas Ludwig is the Director of the German Climate Computing Center (DKRZ) and a Professor at the Universität Hamburg. He holds a doctoral degree and habilitation from the Technische Universität München, with expertise in High-Performance Computing (HPC), energy efficiency, and data storage systems. His research focuses on optimizing parallel systems, storage technologies, and computational efficiency for climate science applications. He leads projects like AIMES and PeCoH, advancing HPC storage and energy-aware computing. Education: Doctoral degree and habilitation from TU München (1988–2001). Chair in Parallel Computing at Universität Heidelberg (2001–2009). Research Interests: HPC, data reduction techniques, energy-efficient systems, parallel I/O optimization, and climate modeling infrastructure. Recent Research Trends: His work emphasizes storage system efficiency, machine learning in HPC, and convergence between HPC and Big Data. Key contributions include frameworks for portability (Vecpar), automated performance tools, and energy-aware storage solutions. Awards: Some publications received recognition, e.g., a Best Paper award in 2014 for work on energy efficiency. However, no personal awards are explicitly listed. Advising & Grants: Supervised numerous theses in HPC, I/O optimization, and energy efficiency. Leads major projects funded by national and international initiatives. Labs/Teams: Heads the DKRZ team providing supercomputing and data management for climate research, collaborating with global institutions like the University of Hamburg and European research networks.

Paolo TrunfioView profile

Professor

• Computer Engineering
• Big Data Analysis
• Machine Learning
• +5 more

Paolo Trunfio is a Professor of Computer Engineering at the University of Calabria, Italy, and co-founder of DtoK Lab S.r.l., an academic spin-off focused on data analysis and distributed systems. He holds a Ph.D. and is affiliated with the DIMES Department, specializing in big data, cloud computing, and high-performance computing (HPC). His research emphasizes scalable data analysis frameworks, edge-cloud continuum solutions, and machine learning applications for social media and disaster monitoring. Trunfio serves as an Associate Editor for ACM Computing Surveys and Journal of Big Data , and is on the editorial boards of several journals including Future Generation Computer Systems . He has authored four influential books, including Programming Big Data Applications (2024) and Data Analysis in the Cloud (2015). His work spans distributed systems, IoT-based smart objects, and exascale computing. Notable projects include the EU-funded eFlows4HPC and ASPIDE initiatives, which focus on HPC workflows and exascale programming models. Trunfio’s publications (over 200 papers) address topics like social media analytics, energy-efficient P2P networks, and parallel data mining. He leads research in urgent computing for disaster response, edge-cloud integration for urban mobility, and AI-driven data analysis. His contributions to cloud frameworks (e.g., JS4Cloud, ParSoDA) and HPC libraries (e.g., DCEx) highlight his expertise in bridging theory and practice in distributed computing ecosystems.

Jonathan FreundView profile

Professor

• Fluid Mechanics
• Biomedical Fluid Dynamics
• Aerodynamic Sound
• +4 more

Jonathan Freund is Professor of Mechanical Science and Engineering and Aerospace Engineering at the University of Illinois at Urbana-Champaign, holding the Donald Biggar Willett Professorship since 2016. He serves as Head of Aerospace Engineering (2020-present) and is Co-Director of the Center for Exascale-enabled Scramjet Design (CEESD). His academic journey began with all three degrees in Mechanical Engineering from Stanford University (B.S. 1991, M.S. 1992, Ph.D. 1998), followed by faculty positions at UCLA (1997-2001) before joining UIUC. Freund's research spans fluid mechanics with applications in biomedical systems, aeroacoustics, and materials science. His work focuses on computational modeling of cellular blood flow, jet noise control, plasma-coupled combustion, uncertainty quantification, and nanoscale material processing. He develops advanced simulation tools to investigate phenomena ranging from atomically thin liquid films to spacecraft propulsion systems. His laboratory leverages high-performance computing to solve complex multiphysics problems requiring exascale capabilities. Analysis of his recent publications reveals a strong emphasis on computational fluid dynamics applied to biological systems (35%), aeroacoustics and jet noise (25%), materials processing at nanoscale (20%), and uncertainty quantification methods (20%). His work consistently bridges fundamental fluid mechanics with practical engineering applications, particularly in medical technologies and advanced propulsion systems. Donald Biggar Willett Professor (2016-present) Kritzer Faculty Scholar (2011-2016) Fellow of the American Physical Society (2011) Campus Excellence in Faculty Mentoring Award (2017) APS DFD Gallery of Fluid Motion Winner (2000) Associate Fellow of AIAA (2012) Freund has advised numerous graduate students and received multiple teaching honors including the Engineering Council Award for Excellence in Advising (2008, 2012) and repeated recognition on the List of Excellent Teachers. His research has been supported by agencies including the Department of Energy's National Nuclear Security Administration. He leads the CEESD center which develops physics-faithful predictive simulations for scramjet design using advanced high-temperature composite materials.

George BosilcaView profile

Research Professor

• Distributed Algorithms
• Parallel Programming Paradigms
• High Performance Computing
• +3 more

George Bosilca is a Research Professor at the University of Tennessee, Knoxville, affiliated with the Department of Electrical Engineering and Computer Science and the Innovative Computing Laboratory. He holds a PhD in Computer Science (University of Paris XI, 2004) and an MS in Math and Computer Science (University of Paris XI, 1999). His research focuses on distributed algorithms, parallel programming paradigms, performance modeling/optimization, and resilience in programming models. He contributes to exascale computing initiatives through projects like PaRSEC and Open MPI. Key research areas include task-based runtimes, MPI standardization for exascale systems, and fault-tolerant distributed computing. His work emphasizes scalable and portable constructs for high-performance applications. Bosilca is involved with the Innovative Computing Laboratory (ICL) and collaborates on projects like the EPEXA ecosystem and Argobots threading framework. Recent publications highlight advancements in asynchronous many-task systems, GPU-accelerated collective operations, and resilience strategies for HPC platforms. His contributions span theoretical frameworks and practical implementations, bridging algorithmic innovation with real-world HPC challenges.

• Volcanology
• Volcanic Hazard Assessment
• Computational Geophysics
• +2 more

Sara Barsotti is a researcher at the National Institute of Geophysics and Volcanology (INGV) specializing in volcanology and volcanic hazard assessment. Her key roles include: Associate Editor for Volcanology at Frontiers in Earth Science Review Editor for Geohazards and Georisks at Frontiers in Earth Science Contributor to the EU Center of Excellence for Exascale in Solid Earth (ChEESE) Member of the EUROVOLC citizen-science initiative Collaborator with European volcano observatories Her research focuses on computational geophysics, volcanic hazard modeling, and operational monitoring systems. She investigates tephra dispersion dynamics, lava flow behavior, and probabilistic hazard assessment using high-performance computing. Her work emphasizes European volcanic systems—particularly Icelandic eruptions—and integrates multidisciplinary approaches to improve crisis management protocols and public safety during volcanic events. Analysis of her recent publications reveals a strong trend toward operationalizing advanced computational methods for real-time hazard assessment. Key developments include exascale computing applications for solid earth simulations, refinement of the Aviation Colour Code system for aviation safety, and citizen-science data integration for eruption monitoring. These efforts consistently target practical risk mitigation strategies during active volcanic crises like the 2021 Fagradalsfjall eruption. Scientific awards: None mentioned in the provided text. While specific advised students or individual grants aren't documented, her leadership in major European projects (ChEESE, EUROVOLC) demonstrates substantial involvement in funded research initiatives. These projects coordinate transnational collaborations involving observatories, research centers, and emergency management agencies across Europe. Barsotti actively participates in integrated European volcano infrastructure teams, contributing to standardized monitoring protocols, hazard communication frameworks, and crisis response systems. Her work bridges institutional observatories (e.g., Icelandic Meteorological Office, INGV sections) with community-based monitoring tools, enhancing data collection and public engagement during volcanic unrest.